PT - JOURNAL ARTICLE
AU - Brown, Noam
AU - Sandholm, Tuomas
TI - Superhuman AI for multiplayer poker
AID - 10.1126/science.aay2400
DP - 2019 Aug 30
TA - Science
PG - 885--890
VI - 365
IP - 6456
4099 - http://science.sciencemag.org/content/365/6456/885.short
4100 - http://science.sciencemag.org/content/365/6456/885.full
SO - Science2019 Aug 30; 365
AB - Computer programs have shown superiority over humans in two-player games such as chess, Go, and heads-up, no-limit Texas hold'em poker. However, poker games usually include six players—a much trickier challenge for artificial intelligence than the two-player variant. Brown and Sandholm developed a program, dubbed Pluribus, that learned how to play six-player no-limit Texas hold'em by playing against five copies of itself (see the Perspective by Blair and Saffidine). When pitted against five elite professional poker players, or with five copies of Pluribus playing against one professional, the computer performed significantly better than humans over the course of 10,000 hands of poker.Science, this issue p. 885; see also p. 864In recent years there have been great strides in artificial intelligence (AI), with games often serving as challenge problems, benchmarks, and milestones for progress. Poker has served for decades as such a challenge problem. Past successes in such benchmarks, including poker, have been limited to two-player games. However, poker in particular is traditionally played with more than two players. Multiplayer games present fundamental additional issues beyond those in two-player games, and multiplayer poker is a recognized AI milestone. In this paper we present Pluribus, an AI that we show is stronger than top human professionals in six-player no-limit Texas hold’em poker, the most popular form of poker played by humans.